65 search results - page 3 / 13 » Gradient Descent for General Reinforcement Learning |
AAMAS
2007
Springer
13 years 5 months ago
2007
Springer
An original Reinforcement Learning (RL) methodology is proposed for the design of multi-agent systems. In the realistic setting of situated agents with local perception, the task o...
ICML
2004
IEEE
13 years 11 months ago
2004
IEEE
LASSO (Least Absolute Shrinkage and Selection Operator) is a useful tool to achieve the shrinkage and variable selection simultaneously. Since LASSO uses the L1 penalty, the optim...
ATAL
2004
Springer
13 years 11 months ago
2004
Springer
Product Distribution (PD) theory is a new framework for controlling Multi-Agent Systems (MAS’s). First we review one motivation of PD theory, as the information-theoretic extens...
ICML
2003
IEEE
14 years 6 months ago
2003
IEEE
Hierarchical reinforcement learning is a general framework which attempts to accelerate policy learning in large domains. On the other hand, policy gradient reinforcement learning...
PKDD
2009
Springer
14 years 9 days ago
2009
Springer
Abstract. Inverse reinforcement learning addresses the general problem of recovering a reward function from samples of a policy provided by an expert/demonstrator. In this paper, w...